Calculate the pooled estimate of variance

  • Thread starter Thread starter chwala
  • Start date Start date
  • Tags Tags
    Estimate Variance
Click For Summary
SUMMARY

The discussion focuses on calculating the pooled estimate of variance using the formula s^2_p = \dfrac{(n_1-1)s_1^2+(n_2-1)s_2^2}{n_1+n_2-2}. The calculated pooled variance for the given sample sizes and variances is 0.627165. Additionally, the discussion includes hypothesis testing using a t-statistic with a significance level of α=0.05, leading to the rejection of the null hypothesis that the mean weight of boys is equal to that of girls. The critical value for the t-test is -1.782, and the computed t-value is -2.5105.

PREREQUISITES
  • Understanding of pooled variance calculation
  • Familiarity with hypothesis testing concepts
  • Knowledge of t-statistics and critical values
  • Basic statistics, including sample sizes and variances
NEXT STEPS
  • Study the derivation and applications of pooled variance in statistical analysis
  • Learn about hypothesis testing using t-tests and their assumptions
  • Explore the implications of rejecting the null hypothesis in practical scenarios
  • Review statistical notation and its importance in hypothesis formulation
USEFUL FOR

Statisticians, data analysts, and students studying statistics who are involved in hypothesis testing and variance analysis.

chwala
Gold Member
Messages
2,828
Reaction score
421
Homework Statement
See attached
Relevant Equations
stats
1648466908376.png

OK, Let me attempt part (i), first,
Here we have;
##s^2_p ##=##\dfrac{ (n_1-1)s_1^2+(n_2-1)s_2^2}{n_1+n_2-2}##

##s^2_p ##=##\dfrac{ (7-1)0.63953+(7-1)0.6148}{7+7-2}##

##s^2_p ##=##\dfrac{3.83718+3.6888}{12}##

##s^2_p ##=##\dfrac{3.83718+3.6888}{12}##

##s^2_p ##=##\dfrac{7.52598}{12}##

##s^2_p ##=##0.627165## its located between the two original variances... correct? i do not have markscheme nor solutions...

* Reading on this topic now...the literature is really confusing on the so called population data (presumably all the n values in a given data set) and sample data...
 
Last edited:
Physics news on Phys.org
i) Your sample sizes are uniform, so there's no need for weighted averages here. Find the variance estimates for both populations and then take their arithmetic mean.
 
nuuskur said:
i) Your sample sizes are uniform, so there's no need for weighted averages here. Find the variance estimates for both populations and then take their arithmetic mean.
Ok mate i.e ##\dfrac {0.63953+0.6148}{2}##= ##\dfrac {1.25433}{2}=0.627165## .

For part (ii), Let, ##μ_1## and##μ_2## be the mean for boys and girls respectively, then
We want to test the hypothesis; as per the question...

##H_0##: ##μ_1##=##μ_2## - Mean weight of boys is equal to mean weight of girls.
##H_A##: ##μ_1##<##μ_2## - Mean weight of boys is less than the mean weight of girls.

Using the t-statistic and also considering that dof =##12##and ##α=0.05## then it follows that the critical value = ##-1.782##
We shall therefore have,
##t##=##\dfrac {2.5429-3.18571}{\sqrt{(0.627165^2(\frac {1}{6}+\frac {1}{6})}}##=##\dfrac {2.5429-3.18571}{0.256040263}##=##-2.5105 < -1.782 ## We thefore Reject the Null hypothesis and accept the Alternative hypothesis.
 
Last edited:
Your notation is overloaded. You likely mean ##\mu _1## for boys and ##\mu _2## for girls. Hypotheses are logical negations of one another. This is not the case right now.
 
nuuskur said:
Your notation is overloaded. You likely mean ##\mu _1## for boys and ##\mu _2## for girls. Hypotheses are logical negations of one another. This is not the case right now.
Amended ...sorry was a bit busy...
 
nuuskur said:
Your notation is overloaded. You likely mean ##\mu _1## for boys and ##\mu _2## for girls. Hypotheses are logical negations of one another. This is not the case right now.
Is it now correct?
 

Similar threads

  • · Replies 2 ·
Replies
2
Views
1K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 5 ·
Replies
5
Views
8K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
5
Views
5K
Replies
1
Views
6K